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http://hdl.handle.net/1893/26397| Appears in Collections: | Computing Science and Mathematics Conference Papers and Proceedings |
| Author(s): | Cambria, Erik Speer, Robert Havasi, Catherine Hussain, Amir |
| Contact Email: | amir.hussain@stir.ac.uk |
| Title: | SenticNet: A publicly available semantic resource for opinion mining |
| Citation: | Cambria E, Speer R, Havasi C & Hussain A (2010) SenticNet: A publicly available semantic resource for opinion mining. In: Commonsense Knowledge: Papers from the AAAI Fall Symposium. Fall Symposium Series Technical Reports, FS-10-02. 2010 AAAI Fall Symposium, Arlington, VA, USA, 11.11.2010-13.11.2010. Menlo Park, CA, USA: AAAI Press, pp. 14-18. http://www.aaai.org/Press/Reports/Symposia/Fall/fall-reports.php |
| Issue Date: | 2010 |
| Date Deposited: | 20-Dec-2017 |
| Series/Report no.: | Fall Symposium Series Technical Reports, FS-10-02 |
| Conference Name: | 2010 AAAI Fall Symposium |
| Conference Dates: | 2010-11-11 - 2010-11-13 |
| Conference Location: | Arlington, VA, USA |
| Abstract: | Today millions of web-users express their opinions about many topics through blogs, wikis, fora, chats and social networks. For sectors such as e-commerce and e-tourism, it is very useful to automatically analyze the huge amount of social information available on the Web, but the extremely unstructured nature of these contents makes it a difficult task. SenticNet is a publicly available resource for opinion mining built exploiting AI and Semantic Web techniques. It uses dimensionality reduction to infer the polarity of common sense concepts and hence provide a public resource for mining opinions from natural language text at a semantic, rather than just syntactic, level. |
| Status: | VoR - Version of Record |
| Rights: | The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. |
| URL: | http://www.aaai.org/Press/Reports/Symposia/Fall/fall-reports.php |
| Licence URL(s): | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved |
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